Novel 3D Culture Systems for Studies of Human Liver Function and Assessments of the Hepatotoxicity of Drugs and Drug Candidates
Abstract
The liver is an organ with critical importance for drug treatment as the disposition and response to a given drug is often determined by its hepatic metabolism. Patient-specific factors can entail increased susceptibility to drug-induced liver injury, which constitutes a major risk for drug development programs causing attrition of promising drug candidates or costly withdrawals in postmarketing stages. Hitherto, mainly animal studies and 2D hepatocyte systems have been used for the examination of human drug metabolism and toxicity. Yet, these models are far from satisfactory due to extensive species differences and because hepatocytes in 2D cultures rapidly dedifferentiate resulting in the loss of their hepatic phenotype and functionality. With the increasing comprehension that 3D cell culture systems more accurately reflect in vivo physiology, in the recent decade more and more research has focused on the development and optimization of various 3D culture strategies in an attempt to preserve liver properties in vitro. In this contribution, we critically review these developments, which have resulted in an arsenal of different static and perfused 3D models. These systems include sandwich-cultured hepatocytes, spheroid culture platforms, and various microfluidic liver or multiorgan biochips. Importantly, in many of these models hepatocytes maintain their phenotype for prolonged times, which allows probing the potential of newly developed chemical entities to cause chronic hep…
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Advanced 3D human hepatocyte culture models improve maintenance of the organotypic microenvironment, including multicellular spheroids and microphysiological systems.
“Advanced 3D human hepatocyte culture models presented in recent years improve the maintenance of the organotypic microenvironment, including multicellular spheroids and microphysiological systems (MPS) [4][5][6][7][8][9] .”
From 3D microperfusion of mesoscale human microphysiological liver models improves functionality and recapitulates hepatic zonation (2023) · cites this paper as [4]
Cites
Matrix elasticity directs stem cell lineage specification
Engler, A. J., Sen, S., Sweeney, H. L., & Discher, D. E. (2006) · Cell · doi:10.1016/j.cell.2006.06.044 · Cited by 13,915 · see citing works
Designing materials for biology and medicine
Langer, R., & Tirrell, D. A. (2004) · Nature · doi:10.1038/nature02388 · Cited by 3,198 · see citing works
Concordance of the toxicity of pharmaceuticals in humans and in animals
Olson, H., Betton, G., Robinson, D., Thomas, K., Monro, A., Kolaja, G., Lilly, P., Sanders, J., Sipes, G., Bracken, W., et al. (2000) · Regulatory Toxicology and Pharmacology · doi:10.1006/rtph.2000.1399 · Cited by 2,050 · see citing works
Lessons learned from the fate of AstraZeneca's drug pipeline: a five-dimensional framework
Cook, D., Brown, D., Alexander, R., March, R., Morgan, P., Satterthwaite, G., & Pangalos, M. N. (2014) · Nature Reviews Drug Discovery · doi:10.1038/nrd4309 · Cited by 1,344 · see citing works
Godoy, P., Hewitt, N. J., Albrecht, U., Andersen, M. E., Ansari, N., Bhattacharya, S., Bode, J. G., Bolleyn, J., Borner, C., Böttger, J., et al. (2013) · Archives of Toxicology · doi:10.1007/s00204-013-1078-5 · Cited by 1,280 · see citing works
Maschmeyer, I., Lorenz, A. K., Schimek, K., Hasenberg, T., Ramme, A. P., Hübner, J., Lindner, M., Drewell, C., Bauer, S., Thomas, A., et al. (2015) · Lab on a Chip · doi:10.1039/c5lc00392j · Cited by 861 · see citing works
Carey, E. J., Ali, A. H., & Lindor, K. D. (2015) · The Lancet · doi:10.1016/s0140-6736(15)00154-3 · Cited by 735 · see citing works
McKenzie, R., Fried, M. W., Sallie, R., Conjeevaram, H., Di Bisceglie, A. M., Park, Y., Savarese, B., Kleiner, D., Tsokos, M., Luciano, C., et al. (1995) · New England Journal of Medicine · doi:10.1056/nejm199510263331702 · Cited by 616 · see citing works
Wagner, I., Materne, E.-M., Brincker, S., Süßbier, U., Frädrich, C., Busek, M., Sonntag, F., Sakharov, D. A., Trushkin, E. V., Tonevitsky, A. G., et al. (2013) · Lab on a Chip · doi:10.1039/c3lc50234a · Cited by 476 · see citing works
Multi-cell type human liver microtissues for hepatotoxicity testing
Messner, S., Agarkova, I., Moritz, W., & Kelm, J. M. (2013) · Archives of Toxicology · doi:10.1007/s00204-012-0968-2 · Cited by 319 · see citing works
Treyer, A., & Müsch, A. (2013) · Comprehensive Physiology · doi:10.1002/cphy.c120009 · Cited by 252 · see citing works
Novel human hepatic organoid model enables testing of drug-induced liver fibrosis in vitro
Leite, S. B., Roosens, T., El Taghdouini, A., Mannaerts, I., Smout, A. J., Najimi, M., Sokal, E., Noor, F., Chesne, C., & van Grunsven, L. A. (2016) · Biomaterials · doi:10.1016/j.biomaterials.2015.11.026 · Cited by 234 · see citing works
Jennen, D. G. J., Magkoufopoulou, C., Ketelslegers, H. B., van Herwijnen, M. H. M., Kleinjans, J. C. S., & van Delft, J. H. M. (2010) · Toxicological Sciences · doi:10.1093/toxsci/kfq026 · Cited by 220 · see citing works
Competency of different cell models to predict human hepatotoxic drugs
Gómez-Lechón, M. J., Tolosa, L., Conde, I., & Donato, M. T. (2014) · Expert Opinion on Drug Metabolism & Toxicology · doi:10.1517/17425255.2014.967680 · Cited by 199 · see citing works
James, L. P., Letzig, L., Simpson, P. M., Capparelli, E., Roberts, D. W., Hinson, J. A., Davern, T. J., & Lee, W. M. (2009) · Drug Metabolism and Disposition · doi:10.1124/dmd.108.026195 · Cited by 175 · see citing works
Imura, Y., Sato, K., & Yoshimura, E. (2010) · Analytical Chemistry · doi:10.1021/ac100806x · Cited by 172 · see citing works
Heslop, J. A., Rowe, C., Walsh, J., Sison-Young, R., Jenkins, R., Kamalian, L., Kia, R., Hay, D., Jones, R. P., Malik, H. Z., et al. (2017) · Archives of Toxicology · doi:10.1007/s00204-016-1694-y · Cited by 141 · see citing works
Liver tissue engineering and cell sources: issues and challenges
Palakkan, A. A., Hay, D. C., PR, A. K., TV, K., & Ross, J. A. (2013) · Liver International · doi:10.1111/liv.12134 · Cited by 130 · see citing works
Hemodynamic flow improves rat hepatocyte morphology, function, and metabolic activity in vitro
Dash, A., Simmers, M. B., Deering, T. G., Berry, D. J., Feaver, R. E., Hastings, N. E., Pruett, T. L., LeCluyse, E. L., Blackman, B. R., & Wamhoff, B. R. (2013) · American Journal of Physiology-Cell Physiology · doi:10.1152/ajpcell.00331.2012 · Cited by 108 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Bell, C. C., Dankers, A. C. A., Lauschke, V. M., Sison-Young, R., Jenkins, R., Rowe, C., Goldring, C. E., Park, K., Regan, S. L., Walker, T., et al. (2018) · Toxicological Sciences · doi:10.1093/toxsci/kfx289 · Cited by 327 · see citing works
Self-citationThree-dimensional liver-derived extracellular matrix hydrogel promotes liver organoids function
Saheli, M., Sepantafar, M., Pournasr, B., Farzaneh, Z., Vosough, M., Piryaei, A., & Baharvand, H. (2018) · Journal of Cellular Biochemistry · doi:10.1002/jcb.26622 · Cited by 148 · see citing works
Bioprinting technologies for disease modeling
Memic, A., Navaei, A., Mirani, B., Cordova, J. A. V., Aldhahri, M., Dolatshahi-Pirouz, A., Akbari, M., & Nikkhah, M. (2017) · Biotechnology Letters · doi:10.1007/s10529-017-2360-z · Cited by 73 · see citing works
Engineering Liver Microtissues for Disease Modeling and Regenerative Medicine
Huang, D. (., Gibeley, S. B., Xu, C., Xiao, Y., Celik, O., Ginsberg, H. N., & Leong, K. W. (2020) · Advanced Functional Materials · doi:10.1002/adfm.201909553 · Cited by 65 · see citing works
In Vitro Three‐Dimensional Liver Models for Nanomaterial DNA Damage Assessment
Llewellyn, S. V., Niemeijer, M., Nymark, P., Moné, M. J., van de Water, B., Conway, G. E., Jenkins, G. J. S., & Doak, S. H. (2021) · Small · doi:10.1002/smll.202006055 · Cited by 41 · see citing works
Lee, H.-J., Son, M. J., Ahn, J., Oh, S. J., Lee, M., Kim, A., Jeung, Y.-J., Kim, H.-G., Won, M., Lim, J. H., et al. (2017) · Acta Biomaterialia · doi:10.1016/j.actbio.2017.09.041 · Cited by 47 · see citing works
Wesseler, M. F., Taebnia, N., Harrison, S., Youhanna, S., Preiss, L. C., Kemas, A. M., Vegvari, A., Mokry, J., Sullivan, G. J., Lauschke, V. M., et al. (2023) · Acta Biomaterialia · doi:10.1016/j.actbio.2023.09.022 · Cited by 39 · see citing works
Self-citationLiu, J., Li, R., Xue, R., Li, T., Leng, L., Wang, Y., Wang, J., Ma, J., Yan, J., Yan, F., et al. (2018) · Advanced Biosystems · doi:10.1002/adbi.201800110 · Cited by 23 · see citing works
From NAFLD to MAFLD: Aligning Translational In Vitro Research to Clinical Insights
Gatzios, A., Rombaut, M., Buyl, K., De Kock, J., Rodrigues, R. M., Rogiers, V., Vanhaecke, T., & Boeckmans, J. (2022) · Biomedicines · doi:10.3390/biomedicines10010161 · Cited by 15 · see citing works
- Authors
- Lauschke, V. M., Hendriks, D. F. G., Bell, C. C., Andersson, T. B., & Ingelman-Sundberg, M.
- Affiliations
- Section of Pharmacogenetics, Department of Physiology and Pharmacology, Karolinska Institutet, SE-17177 Stockholm, Sweden
- Venue
- Chemical Research in Toxicology
- Publisher
- American Chemical Society (ACS)
- Published
- 2016-09-23
- Volume
- 29
- Issue
- 12
- Pages
- 1936-1955
- ISSN
- 0893-228X
- 1520-5010
- Cited by
- 226
- References
- 19
- Language
- en
- Funders
- AstraZeneca
- Vetenskapsr?det
- European Commission (115336)
- Directorate-General for Research and Innovation
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review